The inventive concept relates generally to image sensors. More particularly, the inventive concept relates to correlated double sampling (CDS) circuits and analog-to-digital converters (ADC) using dithering, as well as image sensors including same.
An image sensor is a device that captures an image when an optical signal (e.g., visual light) interacts with a semiconductor material. There different kinds of image sensors, but important commercial types of image sensors include complementary metal-oxide semiconductor (CMOS) image sensors and charge-coupled device (CCD) image sensors. The CMOS image sensor consumes relatively less power that the CCD image sensor, and has been widely adapted for use within mobile phones, digital cameras, and other handheld devices.
In certain conventional implementations, CMOS image sensors transform “a pixel signal” (VPIX) that is provided in column units using a single-slope (SS), column parallel (CP), ADC in conjunction with multiple-ramp CDS circuits. A multiple-ramp CDS mechanism may operate according to a pure digital method, or a dual analog-digital method. However, in both of these methods a first ramp is used to transform a reset signal and a second ramp is used to transform an image signal. The two transformed signals are then subtracted one from the other using conventionally understood digital subtraction processes.
When a large number of signal transformations, such as the reset signal and/or image signal transformations described above, occur simultaneously, certain “common signals” shared by the SS-CP ADC (e.g., a ramp signal (VRAMP), a power supply signal, a bias signal, and/or a ground signal) may undesirably fluctuate. In particular, since the reset signal usually has a less wide variation range than the image signal, the first ramp is likely to be most adversely influenced by fluctuation in the common signals. As a result, errors (e.g., erroneously interpreted signal transitions) may arise in the reset and/or image signals, and such errors are not effectively removed by conventional digital subtraction processes. Such residual signaling errors are manifest as signal dependent noise, degradation in the linear response, gain error, fixed pattern noise (FPN), and/or debased signal-to-noise ratio for the ultimately generated image.